Considering the unique landscape of Africa, the evolution of computing infrastructure and its application is indeed undergoing a significant transformation. This transition is primarily driven by the increasing complexity of workloads, particularly in Artificial Intelligence (AI), and the necessity for hardware that can efficiently manage these demands. 

The reliance on the Central Processing Unit (CPU) for a broad spectrum of computational tasks has been challenged by the rise of applications requiring more specialised processing capabilities. This has led to the development and adoption of the Graphic Processing Unit (GPU), which excels in parallel processing and matrix multiplications, essential for rendering graphics in gaming and performing the computational heavy lifting in AI, enabling ‘deep learning’ – turning data into accurate insights and predictions.

The proliferation of ‘deep learning’ has prompted global tech companies to innovate further, creating hardware specifically tailored to these workloads, such as the Cloud Tensor Processing Unit (TPU) from Google – designed to fast track the process of machine learning. These developments signal a shift towards creating hardware optimised for specific tasks, including future devices designed for Generative AI (GenAI).

For Africa, this global trend offers both challenges and opportunities. While the continent may primarily be a consumer of such advanced hardware, given the substantial investment required for development, there is a crucial role for Africa to play beyond consumption. 

African developers and researchers should actively engage in creating applications that address the continent's unique needs. This is especially pertinent in areas where existing models fall short, such as in recognising local languages, which are often underrepresented in Large Language Models (LLMs), and in acknowledging the diversity of African skin tones, which are not adequately represented in many vision foundation models.

To mitigate these gaps and ensure the development of trustworthy, locally relevant solutions, African innovators must leverage the global infrastructure while tailoring applications to meet regional nuances. This involves not only addressing cultural and linguistic diversity but also navigating the varied regulatory landscapes across the continent. 

Privacy laws and regulatory frameworks differ significantly among African nations, influencing how public infrastructure can be utilised in compliance with local regulations.

Furthermore, the advancements in quantum computing by African institutions such as the University of Witwatersrand and the University of Kwa-Zulu Natal present another frontier for the continent. These capabilities offer promising applications in cryptography and other fields, emphasising the importance of the industry staying abreast of and engaging with academic research to harness these emerging technologies.

Therefore, the path forward for Africa in this evolving computational landscape involves not just adapting global technologies but actively participating in shaping the next wave of computing solutions. This will require robust industry-research partnerships and a commitment to developing applications that are both globally innovative and deeply attuned to the needs of the African context. Clients should identify key business led applications that can be executed, leveraging the Deloitte Gen AI dossier can accelerate these efforts - key in localising and establishing competitive advantage in using modern technologies.